Monitoring snowpack depth is essential in many applications at regional and global scales.
Space-borne passive microwave (PMW) remote sensing observations have been widely …

Current methods for retrieving SWE (snow water equivalent) from space rely on passive
microwave sensors. Observations are limited by poor spatial resolution, ambiguities related …

Accurate snowpack simulations are critical for regional hydrological predictions, snow
avalanche prevention, water resource management, and agricultural production, particularly …

River discharge is one of the most critical renewable water resources. Accurately estimating
river discharge with land surface models (LSMs) remains challenging due to the difficulty in …

A key variable describing the mass of seasonal snow cover is snow water equivalent (SWE),
which plays an important role in hydrological applications, weather forecasting and land …

This study explores the use of a support vector machine (SVM) as the observation operator
within a passive microwave brightness temperature data assimilation framework (herein …

A new snow reanalysis method is presented that is designed to jointly assimilate Landsat-
and MODIS-derived (MODSCAG) fractional snow covered area (fSCA) to characterize …

Global monitoring of soil moisture and snow is now available through various satellite
observations from optical, microwave, and gravitational sensors. However, very few …

This study assessed the sensitivity and uncertainty interval of the Noah land surface model
with multiparameterization (Noah‐MP) using observed meteorological data from eight sites …

This study first compares two different passive microwave snow water equivalent (SWE)
retrievals, namely the retrieval from the Suomi National Polar-orbiting Partnership (S-NPP) …